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DeepSeek-V3.2: Reasoning-Focused Large Language Model
DeepSeek-V3.2 was released by DeepSeek on December 1, 2025. It is an evolution of the earlier V3.2-Exp model, released on September 29, 2025, and comes in both main and "Speciale" variants for research and production use.
DeepSeek-V3.2 is a transformer‑based LLM that uses a sparse Mixture‑of‑Experts architecture plus a custom “DeepSeek Sparse Attention” mechanism to cut compute while keeping quality high. It targets tasks like coding, math, research assistance, and multi‑step reasoning, and is designed to power autonomous agents and tool‑calling workflows rather than just simple chat.
DeepSeek-V3.2 Efficiency and Performance
DeepSeek-V3.2 was built on a Mixture-of-Experts (MoE) framework with 671 billion total parameters, but activates only about 37 billion per token for efficiency. This model is able to handle long contexts (up to 128K+ tokens) more cheaply than dense‑attention models, while keeping benchmark performance similar to or better than V3.1.
Benchmarks and reports describe it as competitive with top‑tier frontier models (like GPT‑5.1 or Gemini 3 Pro) on reasoning‑heavy tasks, especially in its higher‑compute variants.
Variants of DeepSeek-V3.2
- DeepSeek-V3.2: Mainstream version optimized for general-purpose reasoning and everyday deployment.
- DeepSeek-V3.2-Speciale: High-compute variant for advanced tasks, excelling in specialized domains but with higher token usage; temporarily API-only until mid-December 2025 for evaluation.
Comparison of DeepSeek-V3.2 and Other Advanced Models
DeepSeek-V3.2 matches or exceeds frontier models like GPT-5.1 and Gemini 3 Pro on key benchmarks, particularly in math, coding, and long-context tasks. Here's a summary of the comparison between these models:
| Aspect | DeepSeek-V3.2 | DeepSeek-V3.2-Speciale | GPT-5.1 | Gemini 3 Pro |
| Developer | DeepSeek AI (China) | DeepSeek AI (China) | OpenAI (USA) | Google DeepMind (USA) |
| Release Date | December 1, 2025 | December 1, 2025 (API-only initially) | November 12, 2025 | November 17, 2025 |
| Parameters | 671B total (MoE, ~37B active) | 671B total (MoE, ~37B active) | Undisclosed (estimated >1T) | Undisclosed (estimated >1T) |
| Context Length | 128K-131K tokens | 128K-131K tokens (optimized for longer reasoning) | >128K tokens (likely 1M+) | 1M+ tokens (up to 2M in some modes) |
| Key Features | Reasoning-first, DeepSeek Sparse Attention (DSA) for efficiency, integrated tool-use with thinking, agentic workflows | High-compute reasoning variant, relaxed length constraints for complex tasks, excels in math/coding olympiads | Smarter reasoning, better tone/personality, strong generalist performance, multimodal | Native multimodality, state-of-the-art reasoning/tool use, long-context mastery, creative/strategic planning |
| Access | Open-source (MIT), Hugging Face, API, free app/web | API-only initially (open mid-Dec 2025) | API/subscription (paid tiers) | API/subscription (paid tiers) |
| AIME 2025 (Math) | 93.1% | 96.0% | 94.6% | 95.0% (100% with code execution) |
| HMMT 2025 (Math) | 92.5% | 99.2% | N/A | 97.5% |
| SWE-Bench Verified (Coding) | ~67-73% (varies by eval) | 73.1% | ~62-70% (inferred) | 76.2% |
| Terminal-Bench 2.0 (Agentic Coding) | 46.4% | Higher (optimized) | 35.2% | 54.2% |
How to Access DeepSeek-V3.2
It can be accessed through free and paid channels, including web interfaces, mobile apps, APIs, and direct downloads for local deployment.
- HIX AI: Here we offer instant and easy access to DeepSeek-V3.2, and the earlier versions like DeepSeek-V3 and DeepSeek-R1.
- Web and Mobile App: Another way for casual users to interact with DeepSeek-V3.2 is via DeepSeek's official platforms, including the official website https://www.deepseek.com/ and the DeepSeek mobile app.
- API Access: DeepSeek's API is OpenAI-compatible, making it easy to integrate into apps or scripts.
- Local Deployment: This is a developer-focused approach. You can download the model from the Hugging Face page: https://huggingface.co/deepseek-ai/DeepSeek-V3.2 and run it on your own hardware.
Questions and Answers
What are the main DeepSeek V3.2 variants?
The main production variants are DeepSeek-V3.2 (balanced, “daily driver” model) and DeepSeek-V3.2-Speciale (a higher-end reasoning model targeted at very hard math, coding, and competition-style problems).
How does DeepSeek-V3.2 compare to GPT-5.1 or Gemini 3 Pro in performance?
DeepSeek-V3.2 excels in math/coding and efficiency, rivaling these frontier models at lower costs.
Does DeepSeek-V3.2 support multimodal inputs like images or video?
Currently, DeepSeek-V3.2 supports text inputs only. It's optimized for reasoning over long text/code/documents.
What is the context window of DeepSeek V3.2?
DeepSeek V3.2 inherits a long context window (around 128K tokens) enabled by sparse attention, allowing it to handle hundreds of pages of text in a single prompt.
How does V3.2 compare to previous DeepSeek versions?
V3.2 builds on the V3.1 “Terminus” generation but focuses on efficiency and reasoning behavior rather than raw benchmark jumps, targeting similar or better quality at much lower cost thanks to sparse attention and updated training/alignments.
What is DeepSeek Sparse Attention (DSA) and why does it matter?
DeepSeek Sparse Attention is a fine-grained sparse attention mechanism that reduces the number of attention operations per token, making long-context processing much cheaper while keeping quality close to earlier dense-attention models.